The present invention relates to the field of mobile radio telecommunications, and more particularly, to determining the location of mobile stations within the coverage area of a radio telecommunications network using time of arrival (TOA) estimations.
The problem of determining the location of a mobile station (MS) is of considerable interest. The primary application that is driving this activity is the positioning of E911 callers in the United States. The United States Federal Communications Commission has imposed a requirement wherein operators, by October 2001, must report the position of emergency callers within their service area. Also, the European Union has proposed a similar law for all 112 callers, which is to take affect by January 2003. In parallel, different vendors of mobile communication equipment have presented solutions to this problem to fulfil these legal requirements.
In GSM, four different position location methods have been standardized to enable operators to offer location-based services. Accordingly, in addition to providing the position of emergency callers, it is likely that mobile positioning will open the door into a new dimension of mobile services and applications that use the subscriber position as input. For example, the position of a subscriber can be used to provide the subscriber with information about restaurants in proximity to the subscriber.
The cellular positioning techniques available today can be divided into network based solutions and terminal based, e.g., mobile station based, solutions. A network-based solution standardized in GSM is the Uplink Time-of-Arrival (TOA) positioning method, which does not require changes to the mobile station. A mobile station based solution standardized in GSM is the Enhanced Observed Time Difference (E-OTD) method.
The core measurements performed by the mobile station to support the E-OTD location method are Time-of-Arrival (TOA) measurements. The mobile station listens to the broadcast control channel (BCCH) carrier of a certain cell and measures the TOA of bursts relative to its own time base. OTD values are formed by subtracting the TOA measurement of a neighbor cell from the TOA measurement of the serving cell. To obtain an accurate position of the mobile station, the TOA""s must be estimated with a high accuracy. For example, a TOA error of 1 bit (i.e. 1 sampling point) corresponds to approximately 1100 meters range error in the position estimation.
For TOA estimation, the mobile station can use normal bursts, synchronization bursts, dummy bursts or a combination thereof. It is not necessary to synchronize to the neighbour base station in order to perform the TOA measurements. The TOA measurement strategy is similar to the neighbour cell measurements in GSM, i.e., where the mobile station is required to perform neighbour cell measurements (e.g. signal strength measurements) in order to find possible candidates for a handover. In principle, the TOA measurements and the neighbor cell signal strength measurements can be made in parallel. The mobile station can be provided with assistance data by the network, which allows predicting the TOA value together with an uncertainty. This defines a correlation search window within which the TOA is expected to be. Therefore, the mobile station knows when to measure the TOA for a particular signal and can schedule the TOA measurements for the individual links accordingly. For more information regarding correlation windows, the interested reader should refer to U.S. patent application Ser. No. 09/186,192 xe2x80x9cImprovements In Downlink Observed Time Difference Measurementsxe2x80x9d by A. Kangas et al., which is herein expressly incorporated by reference.
The choice between synchronization bursts or normal bursts depends, e.g., on the requested response time and the mode of the mobile station. Although the synchronization bursts offer the best correlation properties, these bursts occur very infrequently, i.e., only once every 10 TDMA frames, whereas normal bursts are available at most 8 times per frame. To enable a quick measurement response from the mobile station in dedicated mode, e.g. during emergency calls, it may therefore be necessary to measure on normal bursts.
One problem for TOA estimation is that a mobile station must be able to hear a sufficient number of base stations. The signal strength from neighboring base stations may be very low, resulting in a low signal-to-noise ratio, typically xe2x88x9210 dB. Multipath propagation is also a problem. The multipath propagation channel sets the limit on the estimation accuracy. In co-pending U.S. patent application Ser. No. 09/354,175 xe2x80x9cEfficient Determination of Time of Arrival of Radio Communication Signalsxe2x80x9d by E. Larsson et al., which is herein incorporated by reference in its entirety, a simple TOA estimation algorithm with very low complexity is described for estimating TOA at low signal-to-noise ratios. This algorithm is based on the Incoherent Integration (ICI) with Multipath Rejection (MPR) principle presented in International Patent Publication WO-9927738, which is also incorporated herein by reference in its entirety.
In accordance with the ICI principle described in the above-identified International Patent Publication, the received burst i is first correlated with the known training sequence, to obtain the correlation result ci(k); as indicated below in equation (1):
ci(k)={tilde over (b)}i(k)*TS(k)ixe2x80x83xe2x80x83(1)
where {tilde over (b)}i(k) is the received, de-rotated burst, TS(k) is the known training sequence contained in the burst {tilde over (b)}i(k) and * is the correlation operator. This correlation is performed for a number of M received bursts. The absolute squares of the M correlation results ci(k) are summed, as shown in equation (2).
"psgr"(k)=xcexa3i=oMxe2x88x921|ci(k)|2.xe2x80x83xe2x80x83(2)
The effect of this summation is that the noise in the correlation result is reduced and the maximum (i.e. the TOA) is more likely to be detected. Performing a weighted summation can increase the detection probability, per equation (3):
"psgr"(k)=xcexa3i=oMxe2x88x921wi|ci(k)|2,xe2x80x83xe2x80x83(3)
where the weights wi are based on the estimated SNR. Since the weights wi are difficult to estimate, an alternative ICI method based on the maximum likelihood criterion, also described in co-pending U.S. patent application Ser. No. 09/354,175, is presented in equation (4) below:
xe2x80x83"psgr"log(k)=xcexa3i=oMxe2x88x921log(EsEbixe2x88x92|ci(k)|2),xe2x80x83xe2x80x83(4)
where ES is the energy of TS(k) and Ebi is the energy of {tilde over (b)}i(k). The sum of logarithms is the logarithm of the product and since the logarithm is a monotonic function, the maximum (or minimum) of log (axc2x7bxc2x7c) is the maximum (or minimum) of (axc2x7bxc2x7c). Therefore, equation (4) reduces to:
"psgr"logi(k)="psgr"log(ixe2x88x92l)(k)(EsEbixe2x88x92|ci(k)|2),xe2x80x83xe2x80x83(5)
The minimum value of the cost function, as illustrated above in equation (5), kmin, is the desired TOA in sampling point units. With the detected kmin, an estimate of the channel impulse response is performed for each burst and interpolated to give the desired resolution.
FIGS. 1 and 2 respectively illustrate the TOA estimation performance of the ICI algorithm in a static one-peak channel with additive White Gaussian noise (AWGN) and Co-channel interference (CCI). The Figures illustrate the root-mean-square error (RMSE, 90%) in microseconds as function of signal-to-noise ratio ES/N0 (FIG. 1) and C/I (FIG. 2) for a different number of GSM normal bursts used in the incoherent integration process. The results illustrated in FIGS. 1 and 2 assume that the transmitted bursts are GSM normal bursts and that the receiver assumes that GSM normal bursts have been transmitted.
As illustrated in FIG. 1, the TOA estimation error is characterized by a large scale error region at low SNR dominated by outliers uniformly distributed across the correlation window, a small-scale error region at high SNR, and a transition region in which large outliers may occur, but with low probability. The breakpoint SNR value between the low and high error region can be shifted to lower SNR""s by increasing the number of bursts used for the TOA estimation. For example, FIG. 1 illustrates that using one normal burst it is possible to estimate a TOA for ES/N0 greater than 1 dB, for 2 bursts it is possible to estimate a TOA for ES/N0 greater than xe2x88x922 dB and for 4 bursts it is possible to estimate a TOA for ES/N0 greater than xe2x88x925 dB, etc. Every doubling of the number of bursts results in a performance improvement of approximately 3 dB. By comparing FIGS. 1 and 2, it can be seen that the TOA error estimation for CCI is similar to that described above with respect to AWGN except that the breakpoint is about 1-2 dB worse for CCI.
An evolution of the GSM system will be the introduction of EDGE (Enhanced Data Rates for Global Evolution), also known as GSM++. EDGE makes it possible for existing GSM operators to provide high-speed mobile multimedia communications using the existing Time Division Multiple Access (TDMA) scheme, i.e., 200 kHz carriers with frequency bands of today; 800, 900, 1800 and 1900 MHz.
To achieve a higher data rate using EDGE, the modulation scheme normally used for GSM, i.e., Gaussian Minimum Shift Keying (GMSK) is changed to 8 phase shift key (8PSK) in EDGE. In such a scenario, GSM and EDGE modulated signals will co-exist. This will have an impact on the design and performance of TOA estimation algorithms for E-OTD. An implementation of the E-OTD positioning method must take into account that 8PSK modulated signals may co-exist with GMSK modulated signals. This is not only important for EDGE capable mobile stations, it is also important for GSM only mobiles, which will be used in future networks.
In a future network, GSM and EDGE modulated signals may co-exist. The useful signal the mobile station measures may then be either GMSK or 8PSK modulated. The time slot 0 will probably also in the future contain GMSK modulated bursts only (the synchronization channel, broadcast control channel and other common control channels). However, the time slots 1-7 may contain 8PSK modulated (normal) bursts. The EDGE training sequences have been derived from the binary GSM training sequences. The EDGE modulation format however, has been designed such that mutual orthogonality between GSM and EDGE users is obtained. This will have an impact on the TOA estimation algorithm.
FIG. 3A illustrates a simplified equivalent baseband representation of a GSM transmitter, where source and channel coding are omitted to enhance clarity. In the transmitter, coded bits d(k) together with a training sequence are assembled into bursts by Burst Assembly unit 305. The burst data sequence db(k) is differentially encoded to facilitate coherent demodulation by encoder 310. The resulting sequence xcex2(k) is then modulated by GMSK with BT=0.3 (i.e., the 3 dB bandwidth B multiplied by the symbol duration T) by GMSK modulator 315 and transmitted over the radio channel. Although, GMSK is a non-linear modulation scheme, it can be approximated by a linear modulation. It can be shown, that a GMSK modulation of a differentially encoded sequence can be approximated by an amplitude modulated signal of a rotated data sequence exp(jkxcfx80/2) b(k). The linear approximation of the GSM transmitter is illustrated in FIG. 3B. As illustrated in FIG. 3B, coded bits d(k) together with a training sequence are assembled into bursts using Burst Assembly unit 305. The burst data sequence db(k) is multiplied by exp(jkxcfx80/2) by multiplier 320. The pulse shaping filter c0(t) 325 is the main component of the Laurent decomposition of the GMSK modulation.
FIG. 3C illustrates an exemplary EDGE transmitter. Initially, coded bits d(k) together with training sequences are assembled into bursts using Burst Assembly unit 305. In EDGE, the modulation scheme is the linear 8PSK modulation. Accordingly, three consecutive bits of the burst data db(k) are mapped onto one symbol in the I/Q-plane according to a Gray code using Symbol Mapping unit 330. With the same symbol rate as in GSM of 271 ks/s, the bit rate now becomes 813 kb/s. The 8PSK symbols are continuously rotated by 3xcfx80/8 radians per symbol using multiplier 335. Amplitude modulator 340 performs pulse shaping on the rotated symbols. The modulating 8PSK symbols can be represented by Dirac pulses exciting a linear pulse-shaping filter. This filter is the linearized GMSK impulse, i.e. the main component in a Laurent decomposition of the GMSK modulation. Therefore, the spectral properties of the GSM and EDGE signals are basically the same, i.e. the EDGE signal will fit into the GSM spectrum mask.
FIGS. 4A and 4B respectively illustrate receivers for GSM and EDGE signals. As illustrated in FIGS. 4A and 4B, the received signal y(t) is filtered using filter gRC(t) 405. The filtered signal is sampled at a symbol rate of 1/T using sampler 410. The demodulation of the received sequence can be performed by a simple de-rotation, as illustrated by the multiplier 415 in FIGS. 4A and 4B. However, the de-rotation for GSM and EDGE signals is different. The different rotation of GSM and EDGE signals results in mutual orthogonal signals. This orthogonality can be used to blindly detect the modulation scheme. To detect the modulation scheme, the receiver would first de-rotate the received sequence with exp(xe2x88x92jkxcfx80/2), i.e., the rotation applied to GSM Signals, and then perform a correlation with the known training sequence. Secondly, the receiver will use the same received sequence and perform a de-rotation with exp(xe2x88x92jk3xcfx80/8), i.e., the rotation applied to EDGE signals, and perform the correlation with the known training sequence again.
Based on these two correlation results, the receiver can decide if the received signal was an EDGE or GSM signal. This detection of the modulation scheme works for signal-to-noise ratios down to 3-5 dB with a sufficiently high probability. For E-OTD location however, the mobile station must measure the TOA of distant base stations, which, as described above, results in very low signal-to-noise ratios, typically down to xe2x88x9210 dB. Therefore, in an environment where EDGE and GSM signals co-exist, TOA estimation algorithms are desired, which do not require modulation scheme detection. Further, TOA estimation algorithms which operate at low signal-to-noise ratios are desired.
It is an object of the present invention to provide a new, less complex, yet efficient method for performing TOA measurements on an arbitrary combination of GSM and EDGE bursts without requiring the detection of the modulation scheme.
It is also an object of the present invention to implement such a method without requiring new mobile station hardware.
It is further an object of the present invention to provide such a method where the measurements can be made at very low signal-to-noise ratios, and nevertheless ensure a high availability of location services.
It is still another object of the present invention to provide such a method that enables E-OTD measurements to be reported with minimal delay, which is particularly important for a dedicated mode of operation.
In accordance with the present invention, a received signal is initially demodulated by a receiver in accordance with a first demodulation scheme. The demodulated signal is split into two copies. Taking into account the initial demodulation, one of the copies is demodulated in accordance with another demodulation scheme, thereby resulting in a first signal demodulated in accordance with the first demodulation scheme and a second signal demodulated in accordance with a second demodulation scheme. A training sequence is used to correlate the two signals. The correlation results are then summed in a incoherent integration process. The result of the incoherent integration is used to estimate the time of arrival of the received signal.